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Location Tracking1 Multifloor Tracking Algorithms in Wireless Sensor Networks Devjani Sinha Masters Project University of Colorado at Colorado Springs.

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Presentation on theme: "Location Tracking1 Multifloor Tracking Algorithms in Wireless Sensor Networks Devjani Sinha Masters Project University of Colorado at Colorado Springs."— Presentation transcript:

1 Location Tracking1 Multifloor Tracking Algorithms in Wireless Sensor Networks Devjani Sinha Masters Project University of Colorado at Colorado Springs

2 12/3/2005 DevjaniLocation Tracking2 Why Location Tracking is Useful? Adapted from Motetrack presentationpresentation Assist Firefighters in Search/Rescue inside building Often cannot see because of heavy smoke + are unfamiliar with building Use wireless sensors (badge/beacon); GPS does not work in buildings Can greatly benefit from a heads-up display to track their location and monitor safe exit routes Chicago City Council … all buildings more than 80 feet tall must submit electronic floor plans Incident commander can better coordinate rescuers from command post

3 12/3/2005 DevjaniLocation Tracking3 Related work Spot-on (Washington, Jeffrey Hightower and Gaetano Borriello/XeroxParc, Roy Want) RFID, aggregate algorithm Requires customized special software Centralized Motetrack (Harvard Lorincz and Matt Welsh) Motetrack TinyOS/Mote based - decentralized 3D location tracking using radio signal information Distributed/reference signature based. FRSN Location Tracking TinyOS/Mote based - decentralized Multi-Floor Simulation 3D location tracking using radio signal information Signal Strength based

4 12/3/2005 DevjaniLocation Tracking4 Why Motes/TinyOS seems to be the right platform MOTES are small in size Easy to embed in environment and equipment MOTES can operate off of battery + it is low power Resilient to infrastructure failure TinyOS is a well established platform Used by over 150 research groups worldwide Easy to integrate new sensors/actuators Mica2 mote

5 12/3/2005 DevjaniLocation Tracking5 Research Goals Location Tracking Single Floor Use Jeff Rupp's Obstructed Radio Model 2D Hill climbing algorithm Multi Floor Location Tracking (3D) Extend Obstructed Radio Model to 3D Extend Hill climbing algorithm to 3D Analysis Effect of factors such as scaling, height, initial sensor sets GUI to visualize the algorithm and results

6 12/3/2005 DevjaniLocation Tracking6 Modeling and Simulation TinyOS – mote operating system TOSSIM - Simulate TinyOS mote network TinyViz – visual TOSSIM Standard Java application Uses a ‘plug-in’ architecture to allow for expansion Wide array of existing plugins Easy to expand

7 12/3/2005 DevjaniLocation Tracking7 Obstructed Radio Model Plugin Authored by Jeff Rupp, UCCS Plug-in is based in the Radio Model done by Nelson Lee at Berkeley Radio signals are obstructed by varying amounts by different materials Loss in free space over distance Loss due to obstructions like walls, floors, doors, etc. Assumes 60dB equates to a maximum bit error rate

8 12/3/2005 DevjaniLocation Tracking8 Multi Floor model assumptions Assumptions: Identical floor plan for each floor. Floor Height = 10 ft. Identical mote layout for each floor. Mote Height = 10 ft. Attenuation of the floor/ceiling = 20dB. Cubicle attenuation = 15dB Outer Wall attenuation = 35dB

9 12/3/2005 DevjaniLocation Tracking9 Multi floor Setup in the GUI symbol is beacon sensor node. The label is sensor ID. Here small room has one sensor, large room has two. The hallway has 6 sensors. The top one is the sink node which collecting the sensor data.

10 12/3/2005 DevjaniLocation Tracking10 Hill Climbing Algorithm Legend: Red square is actual target location. 4 purple/grey dots are sensors with strongest signals.

11 12/3/2005 DevjaniLocation Tracking11 Hill Climbing Algorithm Based on the initial sensor set, an estimated location, x, is computed. Through perturbation, four neighboring locations from x is calculated and the one with closest estimated signal strengths will be chosen for next round. x

12 12/3/2005 DevjaniLocation Tracking12 Responder Position in GUI Here the red squares are randomly generated firefighter locations. The overlay green squares are estimated locations.

13 12/3/2005 DevjaniLocation Tracking13 Performance: Effect of Scaling Factors Identical results for SF=1 and SF=2 SF=2 increases the avg error and variance in tracking Single FloorMulti Floor

14 12/3/2005 DevjaniLocation Tracking14 Varying Z value for responder Marginal Differences Single Floor

15 12/3/2005 DevjaniLocation Tracking15 Top4 vs. Top3 motes Top3 increases the avg error and variance in tracking Top3 results in zero convergence issues Single FloorMulti Floor

16 12/3/2005 DevjaniLocation Tracking16 Conclusions First Responder Sensor Network software provides an attractive solution to the critical problem of indoor location tracking. Using radio signal information alone, it is possible to determine the location of a roaming node at close to meter-level accuracy. This concept can be developed using small, inexpensive and low-power devices The multi floor model is quite robust to variations in z co-ordinate of responder. Using top 4 beacon motes in the algorithm gives more accurate results

17 12/3/2005 DevjaniLocation Tracking17 Future Work Incorporate Java 3D API in TinyViz 3D Multi Floor display of Responder Positions Live Implementation of Multi Floor FRSN

18 12/3/2005 DevjaniLocation Tracking18 Key References Konrad Lorincz and Li Li, “MoteTrack: A Robust, Decentralized Approach to RF- Based Location Tracking,” Proceedings of the International Workshop on Location and Context-Awareness (LoCA 2005) at Pervasive 2005, May 2005. “MoteTrack: An Indoor Location Detection System for Sensor Networks”, Konrad Lorincz and Li Li, Harvard University. (http://www.eecs.harvard.edu/~konrad/projects/motetrack/)http://www.eecs.harvard.edu/~konrad/projects/motetrack/ “SpotOn: An Indoor 3D Location Sensing technology Based on RF Signal strength” by Jeffrey Hightower and Gaetano Borriello, University of Washington, UW CSE Technical Report #2000-02-02. February 18, 2000 “Radio Signal Obstruction Plug-in for TinyViz” by Jeff Rupp, CS526 from UCCS CO 80933-7150, Fall 2003. “TOSSIM: A Simulator for TinyOS Networks” by Philip Levis and Nelson Lee, (Version 1.0 - June 26, 2003), September 17, 2003.

19 12/3/2005 DevjaniLocation Tracking19 Questions?

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